LLM Comparison

GPT-5.6 Sol vs MiniMax-M3: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Sol vs MiniMax-M3 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Rank #2 vs #17AskClash overall scores 85.6 vs 59.4.
Pricing $5.00/$30.0 vs $0.30/$1.20Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightOpenAI vs MiniMax.

GPT-5.6 Sol vs MiniMax-M3 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricGPT-5.6 SolMiniMax-M3
Overall Score85.659.4
Leaderboard Rank#2#17
RWT9.58.5
Coding Agent Index80.0
HLE47.237.1
GPQA94.192.9
IFEval82.9
SWE-bench80.5
SWE-Pro64.659.0
SWE-Atlas84.0
Terminal-Bench88.866.0
DeepSWE72.7
OSWorld70.1
MCP Atlas74.2
Finance Agent53.848.3
MMMU-Pro83.078.1
ARC-AGI 292.5
Tau285.188.9
MRCR91.5
Input Price (per 1M tokens)$5.00$0.30
Output Price (per 1M tokens)$30.0$1.20
Context Window1M1M
Benchmarks Published1413

GPT-5.6 Sol vs MiniMax-M3 head-to-head charts

GPT-5.6 Sol leads 8 and MiniMax-M3 leads 1 of 9 shared benchmarks. MiniMax-M3 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 SolMiniMax-M3
Overall
85.6GPT-5.6 Sol
59.4MiniMax-M3
RWT
9.5GPT-5.6 Sol
8.5MiniMax-M3
HLE
47.2GPT-5.6 Sol
37.1MiniMax-M3
GPQA
94.1GPT-5.6 Sol
92.9MiniMax-M3
SWE-Pro
64.6GPT-5.6 Sol
59.0MiniMax-M3
Terminal-Bench
88.8GPT-5.6 Sol
66.0MiniMax-M3
Finance Agent
53.8GPT-5.6 Sol
48.3MiniMax-M3
MMMU-Pro
83.0GPT-5.6 Sol
78.1MiniMax-M3
Tau2
85.1GPT-5.6 Sol
88.9MiniMax-M3
GPT-5.6 Sol
Input$5.00
Output$30.0
Workload$11
Context1M
MiniMax-M3
Input$0.30
Output$1.20
Workload$0.54
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More GPT-5.6 Sol and MiniMax-M3 comparisons

Explore how GPT-5.6 Sol and MiniMax-M3 stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.